This paper presents the challenge of training evaluation functions on the basis of deep convolutional neural networks using decent data and computing resources, ...
This paper presents the challenge of training evaluation functions on the basis of deep convolutional neural networks using decent data and computing resources, ...
This paper shows that three loss functions, loss in comparison training, temporal difference errors and cross entropy loss in win prediction, are effective
Alternative Multitask Training for Evaluation Functions in Game of Go · Comparison of Loss Functions for Training of Deep Neural Networks in Shogi.
Shanchuan Wan , Tomoyuki Kaneko: Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks. CIG 2018: 1-8.
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Wan and T. Kaneko. Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks, IEEE CIG 2018; Zhu, H. and T. Kaneko ...
Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks · Conference Paper. August 2018. ·. 59 Reads. ·. 3 Citations.
実験的サービス公開サイトであるCiNii Labsを公開しました。 Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks. DOI PDF 被 ...
Building evaluation functions for chess and shogi with uniformity regularization networks. S Wan, T Kaneko. 2018 IEEE Conference on Computational Intelligence ...
Wan, S., Kaneko, T.: Building evaluation functions for chess and shogi with uniformity regularization networks. In: IEEE Conference on Computational ...